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Record W1571368841 · doi:10.1002/2013eo090011

Working With Strainmeter Data

2013· article· en· W1571368841 on OpenAlexaboutno aff
K. M. Hodgkinson, Duncan Carr Agnew, Evelyn Roeloffs

Bibliographic record

VenueEos · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSeismologyGeologyObservatoryBoreholeSeismometerGeodetic datumTiltmeterNorth American PlateGeodesyPlate tectonicsTectonicsPaleontologyOpticsPhysics

Abstract

fetched live from OpenAlex

Abstract The Plate Boundary Observatory (PBO), the geodetic component of the U.S. National Science Foundation–funded Earthscope program, includes 75 borehole and 6 laser strainmeters ( http://pbo.unavco.org ). The strainmeters are installed at several locations: on the Cascadia forearc in Washington state and on Vancouver Island, Canada; in arrays of two to nine instruments along the North American–Pacific plate boundary in California; at Mount St. Helens; and in Yellowstone National Park. For deformation signals seconds to weeks in duration, strainmeters have a resolution and a signal‐to‐noise ratio superior to those of seismometers and GPS. However, this high sensitivity can introduce nontectonic signals into strain data, presenting data interpretation challenges, especially for borehole strainmeters.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.202
Teacher spread0.146 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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